erik.veninga@v2i.nl

V2i Vors to Innovate

Developments in the field of Reliability

History, insights and an outlook

Erik Veninga – V2i

V2i Vors to Innovate

erik.veninga@v2i.nl

Table of Contents

• What is Reliability?

• The History

• Insights

• An Outlook

• Summarising

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erik.veninga@v2i.nl

Erik Veninga

• Consultant and owner at V2i (Vors to Innovate)

• Applied Research and Consulting on Interconnection Technology and Reliability / Accelerated Lifetime concepts

• Committee member PLOT-FHI: Chairman PLOT Reliability work group, Member CEEES Technical Advisory Board (TAB) for Reliability and Environmental Stress Screening

• Background: Mechanical Eng., Industrial Eng., Electronics industry (10 yrs.) and Applied Research (18 yrs.)

• ASQ Certified Reliability Engineer (CRE), Quality Engineer (CQE) and Six Sigma Black Belt (CSSBB)

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What is Reliability?

“The probability that an item can perform its intended function for a specified interval under stated conditions.” [MIL-STD-721C, 1981]

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To define (product) reliability one must address: 1) A probability of an item functioning as intended 2) An operational interval (time or cycles) 3) A definition of the operating environment

"Fitness for use" [J.M. Juran]

t

t eR )(

λ = failure rate (constant)

t = time

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What is Reliability Engineering?

Contributing to the design objectives:

1) Determine feasibility of meeting design goals

2) Understand the impacts on design performance (single point failures, key design parameters, predominant failure modes / mechanisms)

3) Use proper parts and apply correctly

4) Address all sources of components, materials etc.

5) Validate design

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* Benchmarking Commercial Reliability Practices (1996). Rome, NY: Reliability Analysis Center.

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Reliability in The Victorian Era

• The Dee Bridge disaster

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“Some mysterious vibratory mechanism that transformed the metal's granular structure”

“With the proper care in eliminating in-homogeneities and other imperfections, reliable iron castings "of almost any form and of twenty or thirty tons weight" could be ensured”

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1950s: Rise of Reliability Engineering

Advisory Group on Reliability of Electronic Equipment (AGREE)*:

1. Recommending measures that would result in more reliable equipment

2. Helping to implement reliability programs in government and civilian agencies

3. Disseminating a better education on reliability

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* Collaboration between American Electronics Industry and the Department of Defense (DoD)

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Three important Decades

• From component focus (1950s) to specialisation (1960s) to system reliability / safety (1970s)

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J.H. Saleh, K. Marais / Reliability Engineering and System Safety 91 (2006) 249–256.

System reliability (Plant level) D.S. Peck - Accelerated Testing IC's Software Reliability Redundancy modelling 1st Physics of Failure in Electronics Symposium (RADC) Mosteller - Use of Bayes's theorem to reliability MIL-HDBK-217 "Reliability Prediction of Electronic Equipment" Barlow and Hunter - Markov model for system reliability.

Development RE discipline!

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1980s, 1990s and 21st Century

• During the 1980s the failure rate of many components dropped by factor 10

• Wide use of analytical instrumentation and microscopic techniques like SEM [1980s , →]

• Publication of “Predicting the Reliability of Electronic Equipment” paper [1994]

• Elimination use of defense standards like MIL-HDBK-217 [1994]

• Development of computer simulation methodologies, tools and material models [2000, →]

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Technological progress!

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Time to Common Practice (in Industry)

• 1812 – Bayesian Probability

• 1880 – Markov Chains

• 1889 – Arrhenius Equation

• 1952 – AGREE advisory group

• 1961 – 1st Physics of Failure Symposium

• 1994 – Publication of “Predicting the Reliability of

Electronic Equipment”

• ……

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And what about lessons learned?

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Development still like a Waterfall

Cascading:

• Product requirements

• (Feasibility)

• Concept design

• Detailed design

• Building / integrating

• Testing

• Implementation / use

• …..

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Design for Reliability (DfR)

• Many tools and methods available to support DfR • Did the design approach really change?

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Reliability specification Reliability Testing

What are we doing differently over here?

Cooper:

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“New” Reliability Challenges

The 3 R's for environmental sustainability:

1. Reduce,

2. Reuse, and

3. Recycle

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Waste Management Hierarchy:

- Designed lifetimes

- Remaining Useful Lifetime (RUL)

- 2nd Lifetimes!

“New requirements on new designs, existing products and materials”

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Which Technologies could Help?

• Internet of Things (IoT)

• Big data > Machine Learning (ML)

• Smart dust

• Self-healing

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The Gartner Hype Cycle model for technology innovation [2015].

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Internet of Things (IOT)

• A global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies *

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* Recommendation ITU-T Y.2060 (06/2012) - Internet of Things Global Standards Initiative.

“Relationships between objects, between objects and their environments and objects and humans” – In

essence, all what we need for a reliability assessment!

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Big Data

Data sets that are so large or complex that traditional data processing applications are inadequate

• Increasing level of detail

• From predictive to prescriptive value

• Exponential growth

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“If we have all the reliability related data available: 1) no need to take samples and 2) no concerns about confidence levels”

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Machine Learning (ML)

A method of data analysis that automatically builds and executes analytical models

• Capturing the potential of big data

• Algorithms that iteratively learn from data

• Finding hidden patterns and relations

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“Early detection of failures and degradation in the making”

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Smart Dust

A system of many tiny Micro-Electro-Mechanical Systems (MEMS) such as sensors, robots, or other devices that can detect or actuate

• Usually wirelessly operating in a computer network

• Distributed over an area to perform tasks (e.g. product monitoring / controlling)

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Self-healing Materials

Prognostics & Health Monitoring

Health Management

Self-healing

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Yang, Y., Urban, M., “Self-healing polymeric materials”, Chem. Soc. Rev., 2013, 42, 7446-7467.

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Built in Reliability by Design

Despite all the technological developments, it still does not relieve us of the obligation to built in reliability” by design!

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“Both ways aim to look for failures or behaviour that should not be present!”

You cannot test towards

reliability!

Nor monitor towards

reliability!

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Lastly, Reliability is (almost) for Free

Think, act and grow based on failure mechanisms! Failure modes > what is the failure mechanism? • Loads > which potential mechanisms might be induced • Design > are we preventing or managing all potential

mechanisms? • Root cause analysis > did we find and understood the

underling mechanism?

The difference between a potential lapmiddel and a sustainable measure!

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Summarising

• All the tools available

• Role of technological progress

• Time to common practice

• New challenges and new supporting technologies

• Built in Reliability, only by design

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"Fitness for use" [J.M. Juran]

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Thank you for your Attention

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Erik Veninga | V2i - Vors to Innovate Hoogeind Industrial Estate

Lagedijk 29C, 5705 BX Helmond The Netherlands

E-mail: erik.veninga@v2i.nl Tel: +31(0)6 51531740

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